A.I & Tech notes

Note 1Inhttps://www.linkedin.com/feed/update/urn:li:activity:6314748301786771456Comment:
The key sentence in this article is the following one: “”I don’t think it’s how the brain works,” he said. “We clearly don’t need all the labeled data.”
This is absolutely spot on: And why?
Because we, as humans, we have a learning mechanism based on trust and sociability:
In the case of a small child learning how to differentiate among objects, an example is enough if a trusted source is present, e.g his parents.
When he captures or indicates an object, the trusted source is there to tell him the label to use!
The trusted source then will repeat the operation at will each time the possibility occurs and each time the small child is asking!
Learning is never a lonely process: It is the presence of others which ensures its efficacity, speed and correctness.

Which title was far more correct, i.e. we got:The Massive Hedge Fund Betting on AI
Which generates the following comments from my side:
I read everything and my final opinion is as follow:
If you are using AI then black box solutions which bring you money but you cannot easily understand are feasible outcomes. This is precisely one of the conclusion I have presented two months ago, here:https://www.linkedin.com/feed/update/urn:li:activity:6294165616588922880/
Is this outcome scary? The answer is a twofold one:
First, if you do not care about your risk exposure, then I do not see the issue.
Basically, you are accepting that AI generates black box processes: it is then a question of faith, i.e. you believe- you are sure-that you will always manage to be at the top of those processes.
Second, if you care about your risk exposure and if you want to know what you are doing then better to quickly master the AI stock-picking methodology. This second option seems the most reasonable but she has a cost: You need time and constant human intervention.

Now, if you refer to the original article, i.e. here:https://www.bloomberg.com/news/features/2017-09-27/the-massive-hedge-fund-betting-on-ai
And you take your time to read it, you will notice that Man Group Plc spends an important amount of money to properly use AI in its fund: the team is important and they are constantly working in keeping the AI strategies under scrutiny. More, at the end, the final decision is still in human’s hands and brains.
Clearly, “[…] CEO Ellis says, adopting the technology requires a leap of faith. After all, he says, “If you know exactly what it’s doing and why it is doing it, it’s not machine learning.” He adds, “You have to trust the process. It was scary to take the first jump.”
Now, in a financial world in which the only mantras are cost reduction and speed of execution, the need of human intervention would be interpret as a failure of the AI system. This conclusion is plain wrong!
At the contrary, this just shows how the right solution is to have humans constantly working with AI.
A priori, the issue is not with Man Group approach: They known what they are doing, they have an important research team to help encapsulating AI advises in their funds and they will transmit the costs to their client via usual fees system! The problem is with the new comers- e.g. some robot-advisers for instance- which will use AI without the same Man’s security checks.Answer in this discussion goes exactly in this direction:
Not understanding the investment process from AI driven strategies does not mean that these investments cannot be monitored and checked. Standard risk management can still apply: checking the expos, the levels of risk and looking at the portfolio construction. In the end, the main issue is at the investor side. Are investors ready to put money in “black box” funds? The answer will certainly depend on the track return of these funds in terms of performance and fees.

My answer:
I agree: everything at the end will boil down to return and fees. Nevertheless, I am an economist: What matters for me, is to know what are the characteristics of an equilibrium when plenty of AI funds are simultaneously acting in the stock market.
My concern is, after all, the usual Black Swan effect: each AI fund will pick-up some stocks following its own black-box AI strategy, but then what about the correlation of these boxes/strategies?
Is not a situation like the algo-trading strategies, which resulted in at least one big flash crash in 2010? In other terms, the presence of plenty of these funds can increase the stock market systematic risk. Or am I too gloomy?
Finally, I am still not convinced about the increase in efficiency at the level of the stock market:
Will more active AI funds in the market really improve efficiency?
This sentence sounds weird: “Stocks and other securities will be accurately priced because machines will be able to process more available information.”
Right, but what is the outcome for the economy, in terms of allocation of wealth, of having prices reflecting AI -data-driven-strategies?This make me feel uneasy: how trusts a price structure, that has full meaning only in AI’s eyes? We integrate more data-information-, but often the same amount of data than before but containing more insights, i.e. Humans plus the AI ones.
Here, what about the notion of efficiency, is it “bigger”?
Or simply we need a new notion of efficiency based on the technology we are using? Is this important?
Yes, if we want once again see the price structure as a signal which will guide us in a proper way in allocating our wealth and will it indicate as well possible risks. Or am I wrong?

N.B: Very interesting interview by the way.
And BlackRock is not alone. The disruption of classical asset management offer is under way and it will not be easy to digest: BlackRock & Co have the scale, the infrastructure and the people.
Funnily enough the final outcome is likely to be the usual one: Few major firms controlling (worldwide/occidental countries) the asset management industry in a pure oligopolistic configuration. We will see but this is my 2 cents bet!